Spectroelectrochemistry of Water Oxidation Kinetics in Molecular versus Heterogeneous Oxide Iridium Electrocatalysts

Water oxidation is the step limiting the efficiency of electrocatalytic hydrogen production from water. Spectroelectrochemical analyses are employed to make a direct comparison of water oxidation reaction kinetics between a molecular catalyst, the dimeric iridium catalyst [Ir2(pyalc)2(H2O)4-(μ-O)]2+ (IrMolecular, pyalc = 2-(2′pyridinyl)-2-propanolate) immobilized on a mesoporous indium tin oxide (ITO) substrate, with that of an heterogeneous electrocatalyst, an amorphous hydrous iridium (IrOx) film. For both systems, four analogous redox states were detected, with the formation of Ir(4+)–Ir(5+) being the potential-determining step in both cases. However, the two systems exhibit distinct water oxidation reaction kinetics, with potential-independent first-order kinetics for IrMolecular contrasting with potential-dependent kinetics for IrOx. This is attributed to water oxidation on the heterogeneous catalyst requiring co-operative effects between neighboring oxidized Ir centers. The ability of IrMolecular to drive water oxidation without such co-operative effects is explained by the specific coordination environment around its Ir centers. These distinctions between molecular and heterogeneous reaction kinetics are shown to explain the differences observed in their water oxidation electrocatalytic performance under different potential conditions.


Electrodeposition of IrOx
The IrOx films were all prepared from a solution of iridium salt consisting of 0.2 mmol of Ir 3+ Cl3 hydrate (Fluorochem) and 2 mmol of oxalic acid dehydrate in 30 mL of water. The pH of the iridium salt solution was adjusted to 10 by adding ~5mmol of Na2CO3 (ReagentPlus® ≥ 99.0%), turning the colour of the solution from yellow to green. The volume of the solution was increased to 50 mL by adding more water. The solution was left to rest for 4 days at 35ºC and then stored in the freezer at 4ºC. The electrodeposition of IrOx from this iridium solution was done by soaking a clean FTO on a glass substrate (~1·2·0.2 cm 3 ) and applying a current of 35 µA. To prepare IrOx samples with different thicknesses, the current was applied for 1000 s, 700 s, 500 s, 120 s and 60 s. Polyimide tape was attached on the FTO surface to limit the surface of the IrOx to ~1 cm 2 . This preparation procedure is similar to that in the literature. 6,7 Spectroelectrochemistry Spectroelectrochemistry measurements consisted in probing the absorbance of a sample with an Agilent Technologies Cary 60 UV-Vis spectrometer under different applied potential. The potential was controlled with a Metrohm Autolab PGSTAT101 potentiostat and applied between a platinum mesh (i.e. the counter electrode) and the sample (i.e. the working electrode). The potential at the working electrode was measured with respect to an Ag/AgCl reference electrode saturated with KCl. The absorption was recorded after applying the corresponding potential for ~5 minutes until the current was stable. Each spectrum was measured at least two times until it reached a steady state. The same results were also obtained using an alternative home-built setup integrated by an OceanOptics HL-2000-FHSA halogen light source and a OceanOptics Maya2000Pro spectrometer.
All the potentials are reported versus RHE and were iRu corrected. The potentials versus Ag/AgCl saturated with KCl (EAg/AgCl) were converted into potentials versus RHE (ERHE) as follows:

Equation S1
Where R is the ideal gas constant (8.314 J·mol -1 ·K -1 ), T is the temperature (298 K), F is the Faraday constant (96485 C/mol electrons), z is the number of electrons transferred (1 mol electrons), and EAg/AgCl 0 is the standard potential of the Ag/AgCl reference electrode saturated with KCl. The pH used is 1.2.
All the potentials were corrected by subtracting i·Ru, where i is the current measured at the corresponding potential and Ru is the uncompensated resistance The resistance Ru (between 35 and 40 Ω) was calculated by fitting electrochemical impedance data in the 0.1-1 Hz range with the Randles circuit model.
2.30 · · · · = $%/$%'( + 0.197 + 0.059 · = $%/$%'( + 0.2678 Step-Potential Spectroelectrochemistry Step-potential spectroelectrochemistry measurements (SP-SEC) consisted in probing the absorption during potential cycles of two steps, as represented in Scheme S1. The potential was controlled with a PalmSens3 potentiostat. In parallel, the probe light was produced with a 100 W Bentham tungsten lamp, and its wavelength was selected with two Horiba Scientific OBB monochromators placed before and after the sample. Additionally, a long-pass filter regulated by a mechanical colour wheel (FW101C Thorlabs) stood between the sample and the second monochromator. The probe light was detected by a silicon PIN photodiode (Hamamatsu S3071) and filtered by an optical transient amplifier (Costronics 2004). Finally, both the electrical and optical signals were processed with a digital phosphor oscilloscope (Tektronix DPO 3012) and a DAQ (National Instruments X Series Multifunction). In the SP-SEC measurements, the electrochemical cell and electrodes used were the same as in the spectroelectrochemical experiments above. The oscillations observed in the optical signals (~2s -1 Hz) are considered environmental noise. Scheme S1. Potential steps in a step-potential spectroelectrochemistry measurement (SP-SEC). Consecutively and in cycles, the potential En is applied during 8 s, and the potential En+1 is applied during 5 s. Simultaneously, the absorption difference ΔA of the sample is monitored (ΔA=A(En+1)-A(En)). Figure 3 were performed by applying a potential for 5 s and then switching to open circuit for 8 seconds (zero current) following Scheme S1. During the 8-s period, the open circuit potential of the electrode changes until it plateaus at a constant value.

Spectroelectrochemical deconvolution
Spectroelectrochemical model data ΔAfit(E,λ) was generated in Matlab R2019a with Equations S1-6, where ΔA is the absorption difference as a function of the potential E and the wavelength λ. The model data was built by making for major assumptions. First, the absorption changes were calculated as a sum of independent contributions Ai(E,λ) (Equation S2), where i is the redox transition number. One, two and three absorption contributions were considered in the deconvolution of each data set. Second, the absorption changes were considered linearly proportional to the concentration of the redox state formed at each transition following the Lambert-Beer law (Equation S3), Ci(E). Third, the concentration of the redox state formed at each potential was approximated as a Gaussian distribution over potential (Equation S4), expected to be a good representation of capacitive redox transitions but a less accurate approximation for the onset of catalytic and Faradaic processes if the catalytic depletion of redox states is faster than its electrochemical recovery. Lorentzian distributions were tested to model the concentration changes over potential, but Gaussian distributions were a better fit in all the cases. Fourth, the differential absorption coefficients εi(λ) were calculated from the experimental absorption at three different potentials following Equations S5-7. Positive differential absorption coefficients are expected when the resulting redox state is more absorptive than the starting redox state, and negative differential absorption coefficients are expected in the opposite case.
The model data was fit to the experimental data by adjusting the center (µ), width (σ) and amplitude (A) of the Gaussian distributions (A·Gaussian(µ,σ)) corresponding to the concentration changes over potential of each redox state. The model data was optimised in Matlab with the global minimisation tool GlobalSearch and the solver fmincon. These tools were set to find the minimum difference between the model and the real data (|ΔAreal(E,λ)-ΔAfit(E,λ)|) across all the wavelengths and potentials. Starting with a set of 200 initial trial points, a total of 1000 trial points were examined in each data set, where each point consisted of a different combination of values for the variables A, µ and σ (Equation S4).

Equation S7
The gaussian function in Equation S4 is shown in Equation S8 below: Where x and y are the independent variables consisting on the potential and concentration respectively herein, and A, , and are the fit constants which are adjusted to the experimental results. The latter variables can be correlated with the Nernst equation (Equation S9) and the electrolyte access to the electrochemical active sites: are the concentration of oxidized and reduced species respectively, z is the number of electrons exchanged, T is the temperature, R is the ideal gas constant, and E 0 and E are the standard reduction potential and the reduction potential respectively.

Calibration and calculation of electrochemical active sites
The concentration changes and differential absorption coefficients of the redox states that best fit the spectrelectrochemical data were adjusted with the experimental values of ε1(600 nm), ε2(800 nm) and ε3(460 nm), the differential absorption coefficients at the absorption maxima during the 1 st , 2 nd and 3 rd redox transitions respectively. To calculate these differential absorption coefficients, the current and absorption changes were simultaneously measured during step potential spectroelectrochemistry measurements (SP-SEC), where two potentials with a difference of 50 mV were cyclically applied in consecutive steps of 5 s and 8 s (Scheme S1). When changing the applied potential, the current peaks, in parallel to a change in the absorption ( Figure S5). The current spike is assumed to be mostly due to the oxidation and reduction of states in the catalyst, and the absorption change is assigned to the differential absorption of the newly formed redox state relative to the starting state. In order to estimate the moles of oxidized species formed at each potential interval, we integrated the current spike over time, having subtracted the background current. For the redox transitions 1 and 2, the maximum absorptions changes at 600 nm and 800 nm were plotted against the extracted charges at potential intervals around 0.8 V and 1.3 V vs. RHE respectively, where the corresponding redox transition is the dominant process ( Figure S5). For the redox transition 3, the same methodology was applied using the absorption changes at 460 nm and the charges extracted above 1.2 V but, because it overlaps significantly with the redox transition 2, the charges and absorption corresponding to the latter redox transition were previously subtracted. The differential absorption coefficient corresponding to a oneelectron oxidation per redox transition was taken from the slope of the linear regression ( Figure S6).
The electrochemically active iridium in both catalysts is considered all the iridium detected by spectroelectrochemistry. This is because the UV−vis of these compounds is related to proton-coupled electron-transfer processes that must involve iridium placed either at the electrode−electrolyte interface or, given the porous and nanostructured nature of the films, accessible to the electrolyte. [8][9][10][11][12] To compare the two catalysts, the total amount of electroactive iridium ( Figure 1C) is approximated as the total amount of redox state resulting from the 1 st redox transition. This is done by integrating the 1 st redox transition in Figures S2 and S7 for IrOx and IrMolecular respectively.

Kinetics analysis
The kinetics decays were smoothed with a Savitzky-Golay filter using polynomial order 2 applied to a window of 50-100 points. To derive the lifetimes τ, the optical signal decays were normalized and fit with an initial slope linear regression between 0 and 25% intensity decay, following Equations S10-11:

= 1⁄
Where ΔA is the experimental differential absorption, t is time, k and c are fit constants, and τ is the lifetime calculated from k.     Figure 2A and the model data in Figure S3A. Figure S4. Absorption changes over potential associated to each redox transition of IrMolecular on mesoITO. This data was generated with Equations S2-7 and the sum of the three components at each potential yields the model data in Figure S3A.  A B Figure S6. Dependency of the deconvoluted absorption changes on the extracted charge for each redox transition. The charges are calculated by integrating the reductive peak in Figure S5A and the deconvoluted absorption in Figure S4. The slope of the linear regression is the relative absorption coefficient of the new redox state formed at the corresponding redox transition. The label next to each data point indicates the potential interval where the absorption changes and the charges were measured.  Figure S11. Steady-state current plotted against the concentration of active species in IrOx samples with different electrodeposition times (1000s, 700s, 500s, 120s and 60s) and in IrMolecular. The concentration of active sites is derived from the deconvoluted and calibrated spectrooelectrochemical data ( Figures 2B, S6-8) and the active state is assumed to be the redox state resulting from the 3 rd redox transition.  A B Table S1. Ratio between the concentration of the redox states 1, 2 and 3 in each IrOx and IrMolecular sample. The concentration in moles per cm 2 has been derived from the deconvolution of the spectroelectrochemistry data (Equations S2-7). (*) In IrOx 60s, the first redox transition detected has been considered a combination of redox transitions 1 and 2 in the rest of the samples.